Anonymised case study · Completed professional work

Making candidate research and review more structured.

This case study describes a system built inside a technology business. The company name, candidate data and internal information remain confidential.

Candidate workspace · Fictional example
Profile AReview readyProfile BCheck sourceProfile CCompare
STRUCTURED OVERVIEW

Facts before the decision

Grouped information, visible sources and items to verify before a person moves the process forward.

SourcesHuman review
01

The problem

Finding profiles, comparing information and preparing follow-ups required several tools and a large amount of manual work. The goal was not to automate an HR decision. It was to give professionals a clearer place to do the work.

02

The approach

I started with the real journey: find relevant profiles, collect useful information, compare candidates and prepare the next action. The system followed those steps rather than forcing the work into a generic AI demonstration.

What was built

A tool shaped around the real work.

  • 01A more structured sourcing process
  • 02An interactive dashboard for reviewing profiles
  • 03An assistant for summarising and comparing information
  • 04Follow-up functions designed around the recruitment workflow
Workflow

The assistance stops before the decision.

01

Collect from approved sources

02

Organise profiles and information

03

Assist analysis with links back to sources

04

Keep decisions and communication human

03

Operational value

Research and preparation work could be brought into one coherent interface. Users kept control of decisions, could return to the source information and had better context before taking action.

04

Limits and human control

  • No candidate was accepted or rejected automatically.
  • Information required verification before sensitive use.
  • The organisation needed to control access, sources and evaluation criteria.
  • No performance metric is published without evidence and permission.
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